Various identification systems are widely used in police and judicial practice to solve the problem of matching a sample image obtained under the prescribed procedure and a mark image obtained accidentally.
Typically, a mark-forming body is a person, and therefore, a mark can be a finger mark or a video frame obtained from a security camera and displaying an image of a person. In this case, in order to identify the object, the mark is compared with samples which are a fingerprint, a photograph, or a video frame displaying an image of a person.
Databases used by information retrieval systems usually include an array of samples and an array of marks, and can contain millions of samples and thousands of unidentified marks. Therefore, in research automated information retrieval systems, e.g. automated dactyloscopic information retrieval systems are used.
In comparative studies, information retrieval systems usually compare samples obtained under the prescribed procedure with marks obtained accidentally.
For example, in dactyloscopic research, personal identification systems usually compare fingerprint and/or palmprint and/or footprint images obtained under the prescribed procedure with finger and/or palm and/or foot marks left on various surfaces and obtained accidentally. As applied herein, a fingerprint and/or palmprint and/or footprint , here constituting a sample, is a dactyloscopic image of skin pattern of a finger, palm or foot obtained by impressing or rolling corresponding skin region against a paper surface or dactyloscopic scanner under the condition that the prescribed dactyloscopic procedure is followed. As applied herein, a dactyloscopic card is a personal profile including a set of prints and personal information.
As applied herein, a mark is a dactyloscopic image usually obtained on a scene of the crime and left by an unidentified person by touching a surface with a finger, palm or foot.
As applied herein, a mark card is a card comprising images of all scene of crime marks.
An automated dactyloscopic information retrieval system compares a query dactyloscopic object (i.e. an object to be compared) with the data in the database. Four types of search are usually performed, namely a query print is compared with prints in the array of prints, a query print is compared with marks in the array of marks, a query mark is compared with prints in the array of prints, and a query mark is compared with marks in the array of mark.
As a result of the search, a reference list of objects that may belong to the same person as the query object is formed, the list being intended for further comparison by an expert. With large databases, to ensure sufficient reliability of the search, the list may be expanded , thus increasing the amount of manual labor by operators reviewing the search results. As applied herein, the search reliability is the probability of including into the reference list a predefined number (usually as a percent of the total objects in the database) of the dactyloscopic objects relevant to the query object , i.e. left by the same person. The search reliability should normally be at least 90%
The comparison of a new print with prints in the array of prints in the database is somewhat an ordinary task because the print is usually obtained in stationary conditions using an approved technique ensuring relatively good image quality. Therefore, when comparing prints, the number of candidate records in reference lists is relatively small. That is, two prints belonging to the same person shall be identified with high accuracy.
At the same time, when a print is compared to a mark, or a mark is compared to a print, extensive reference lists have to be formed requiring much labor to ensure sufficient reliability.
In US patent application 2006/0153433 a method for comparing prints is disclosed, the method being used in print matching apparatus for identifying a user. A query print of a user is compared with the print of the same user previously enrolled in the apparatus database, and a match index is determined. If the match index exceeds a verification threshold, the apparatus considers the query print matching with the enrolled print, thus verifying the identity of the user.
According to this method, each print, when enrolled in the apparatus database, is compared to prints in the set of reference prints. Results of this comparison, particularly, the highest match index and the individual verification threshold are stored with each print in the database for further comparisons.
In US 2006/0153433, a “one-to-one” matching is described, and no possibility for searching for the query print in the prints database is disclosed. However, this method, if used in print-to-print and print-to-mark searches, would result in smaller reference lists because of individual verification thresholds used. Nevertheless, to determine an individual verification threshold statistical calculations are used, thus the results are approximate. Consequently, the search results are not error-free, so that irrelevant candidate records may occur in the reference list. Therefore, using this method for a print-to-mark search will not provide required search accuracy.
In US patent application 2004/0062426 an automated fingerprint system and method is disclosed. A query object is compared with each object of the database. Further to the comparison, a match index of the query object (e.g. a fingerprint) and each object of the database is determined, and a reference list associated with this query object is formed by including objects whose match indexes are higher than the predetermined threshold index. Then the reference list is forwarded to the examiner for making visual comparison between the images of the found objects and the query object.
According to the method described above, the comparison can be performed in several levels, each using its own algorithm. In the first level, objects whose pattern features correspond to those of the query object are selected from the database. Then an additional selection can be made by analyzing the strength of match of the selected objects (having the same pattern features as those of the query object) with the query object. The number of objects in the reference list limited in this way will ensure required reliability.
It is important that objects to be compared shall have approximately similar statistical properties. However, this is not necessarily the case even for prints.
It shall be noted that print-to-mark comparison is much more difficult task because, in contrast to prints, marks left in various situations and on various surfaces are processed using various means with different thoroughness. Furthermore, marks vary in area and can be left by different parts of one or more fingers or palm, thus containing a different number of dactyloscopic features. Therefore, when comparing a print with marks in the array of marks, it is difficult to determine which of the marks should be included in the reference list for a given print: sample A with a low match index, or sample B with a high match index. Due to differences in statistical properties of the objects, it is difficult to determine a minimal match index indicating high probability that the mark matches the print, so that this mark shall be included in the reference list for further comparison. Therefore, using only the first level of the described method, it is necessary to form reference lists including a high number of marks to achieve required reliability. To form reference lists with an acceptable number of marks, developers use to voluntary limit this number. However, this obviously leads to lower reliability.
In order to increase the comparison accuracy with the understanding that the desired search reliability is maintained, said method provides the second and third levels in which match probability is determined by further analyzing the reference list obtained in the first level. When evaluating the probability that a query print and a print in the database match, the data obtained by comparison of other prints from the compared print sets can be used. Obviously, these stages in which match probability is determined, when used for a print-to-print search, allow shorter reference list forwarded to an operator for visual examination.
In US 2004/0062426 said second and third levels are used only in print-to-print search. In the case of print-to-mark search, a dactyloscopic card can be compared with a mark card containing scene of crime marks. However, in contrast to the dactyloscopic card, marks in the mark card belong to a single person only with a certain degree of probability because actual scene of crime marks can be left by different people. Therefore, the probability that the query print matches the mark under examination is only slightly influenced by the results of comparison between the remaining prints from the query dactyloscopic card and the remaining marks from the mark card. Thus, using the algorithms of said second and third levels for print-to-mark search will not lead to substantial shortening of the reference list with the understanding that the desired search reliability is maintained.
Also known in the art are systems for comparing an image (e.g. obtained by a camera) of a person's face or its region with corresponding images of identified persons obtained in advance. However, known systems have a number of disadvantages and cannot be used for comparing marks and samples of various nature with sufficient accuracy.
In U.S. Pat. No. 7,324,670 a face image processing apparatus is disclosed. The apparatus compares a region of a human face in an image obtained by a camera with a corresponding region of a face of an identified person previously registered with the apparatus. Using known methods of image recognition, the apparatus determines the similarity measure between the regions. However, this apparatus compares face region images obtained in approximately the same conditions, and cannot provide sufficiently accurate comparison of face images obtained accidentally and in various conditions.
In U.S. Pat. No. 7,266,224 a person recognition apparatus used for personal identification is disclosed. The apparatus compares an image obtained from a camera and biometric data previously stored in the apparatus memory. On receiving the data from a camera, the apparatus compares the data obtained by image processing with the stored data of all previously registered persons, and selects the person most similar to the person shot by the camera. Then the apparatus calculates a similarity of the previously registered person and the person to be identified. If this data match level is higher than the predetermined threshold, the person is regarded as identified, and vice versa.
It should be noted that this threshold is obtained by calculation, that may lead to additional error during the identification.
In the apparatus, the biometric information stored in the memory can be updated, thus reducing the probability of misidentification caused by age-related changes of the person to be identified, or the difference in face size of the person to be identified during advance registration and further identification. To judge whether the biometric information should be updated an updating range is set.
However, such approach allows the reduction of the error probability only when the images of a person to be identified are obtained in similar conditions. When comparing images obtained accidentally, the device cannot provide sufficient identification accuracy.